Force calculations in automated docking: Enzyme-substrate interactions in Fusarium oxysporum Cel7B

Identification of substrate-binding and selectivity-related residues of maltooligosyltrehalose synthase from the thermophilic archaeon Sulfolobus solfataricus ATCC 35092

Maltooligosyltrehalose synthase (MTSase) is a key enzyme in the synthesis of trehalose. Computer simulations using AutoDock and NAMD were employed to assess the substrate-binding and selectivity-related residues of MTSase. We introduced mutations at residues D411, D610, and R614 to determine the substrate-binding residues of Sulfolobus solfataricus ATCC 35092 MTSase, and introduced mutations at residues P402, A406, and V426 to investigate the enzyme's selectivity-related residues. Kinetic studies of D411A, D610A, and R614A MTSases reveal significant reductions in catalytic efficiency and cause increase in the transition-state energy of mutant MTSases, indicating that residues D411, D610, and R614 form hydrogen bonds to the substrate. Compared with wild-type MTSase, the hydrolysis: transglycosylation selectivity ratio was significantly decreased for P402Q and significantly increased for A406S MTSases, while the ratio for V426T MTSase showed little change. The results suggest that P402 and A406 residues are selectivity-related.

Molecular docking of carbohydrate ligands to antibodies: structural validation against crystal structures

Cell surface glycoproteins play vital roles in cellular homeostasis and disease. Antibody recognition of glycosylation on different cells and pathogens is critically important for immune surveillance. Conversely, adverse immune reactions resulting from antibody-carbohydrate interactions have been implicated in the development of autoimmune diseases and impact areas such as xenotransplantation and cancer treatment. Understanding the nature of antibody-carbohydrate interactions and the method by which saccharides fit into antibody binding sites is important in understanding the recognition process. In silico techniques offer attractive alternatives to experimental methods (X-ray crystallography and NMR) for the study of antibody-carbohydrate complexes. In particular, molecular docking provides information about protein-ligand interactions in systems that are difficult to study with experimental techniques. Before molecular docking can be used to investigate antibody-carbohydrate complexes, validation of an appropriate docking method is required. In this study, four popular docking programs, Glide, AutoDock, GOLD, and FlexX, were assessed for their ability to accurately dock carbohydrates to antibodies. Comparison of top ranking poses with crystal structures highlighted the strengths and weaknesses of these programs. Rigid docking, in which the protein conformation remains static, and flexible docking, where both the protein and ligand are treated as flexible, were compared. This study has revealed that generally molecular docking of carbohydrates to antibodies has been performed best by Glide.

A Gibbs free energy correlation for automated docking of carbohydrates

Thermodynamic information can be inferred from static atomic configurations. To model the thermodynamics of carbohydrate binding to proteins accurately, a large binding data set has been assembled from the literature. The data set contains information from 262 unique protein-carbohydrate crystal structures for which experimental binding information is known. Hydrogen atoms were added to the structures and training conformations were generated with the automated docking program AutoDock 3.06, resulting in a training set of 225,920 all-atom conformations. In all, 288 formulations of the AutoDock 3.0 free energy model were trained against the data set, testing each of four alternate methods of computing the van der Waals, solvation, and hydrogen-bonding energetic components. The van der Waals parameters from AutoDock 1 produced the lowest errors, and an entropic model derived from statistical mechanics produced the only models with five physically and statistically significant coefficients. Eight models predict the Gibbs free energy of binding with an error of less than 40% of the error of any similar models previously published.

Automated docking to explore subsite binding by glycoside hydrolase family 6 cellobiohydrolases and endoglucanases

Cellooligosaccharides were computationally docked using AutoDock into the active sites of the glycoside hydrolase Family 6 enzymes Hypocrea jecorina (formerly Trichoderma reesei) cellobiohydrolase and Thermobifida fusca endoglucanase. Subsite -2 exerts the greatest intermolecular energy in binding beta-glucosyl residues, with energies progressively decreasing to either side. Cumulative forces imparting processivity exerted by these two enzymes are significantly less than by the equivalent glycoside hydrolase Family 7 enzymes studied previously. Putative subsites -4, -3, +3, and +4 exist in H. jecorina cellobiohydrolase, along with putative subsites -4, -3, and +3 in T. fusca endoglucanase, but they are less important than subsites -2, -1, +1, and +2. In general, binding adds 3-7 kcal/mol to ligand intramolecular energies because of twisting of scissile glycosidic bonds. Distortion of beta-glucosyl residues to the (2)S(O) conformation by binding in subsite -1 adds approximately 7 kcal/mol to substrate intramolecular energies.

Puckering Coordinates of Monocyclic Rings by Triangular Decomposition

We describe a new method of describing the pucker of an N-member monocyclic ring using N - 3 parameters. To accomplish this, three ring atoms define a reference plane, and the remainder of the ring is decomposed into triangular flaps. The angle of incidence for each flap upon the reference plane is then measured. The combination of these angles is characteristic of the ring's pucker. This puckering coordinate system is compared to existing reduced parameter systems to describe rings using a cyclohexane molecule. We show that this method has the same descriptive power of previous systems while offering advantages in molecular simulations.

Docking studies on glycoside hydrolase Family 47 endoplasmic reticulum alpha-(1-->2)-mannosidase I to elucidate the pathway to the substrate transition state

Alpha-(1-->2)-mannosidase I from the endoplasmic reticulum (ERManI), a Family 47 glycoside hydrolase, is a key enzyme in the N-glycan synthesis pathway. Catalytic-domain crystal structures of yeast and human ERMan1s have been determined, the former with a hydrolytic product and the latter without ligands, with the inhibitors 1-deoxymannojirimycin and kifunensine, and with a thiodisaccharide substrate analog. Both inhibitors were bound at the base of the funnel-shaped active site as the unusual 1C4 conformer, while the substrate analog glycon is a 3S1 conformer. In the current study, AutoDock was used to dock alpha-D-mannopyranosyl-(1-->2)-alpha-D-mannopyranose with its glycon in chair (1C4,4C1), half-chair (3H2,3H4,4H3), skew-boat (OS2,3S1,5S1), boat (2,5B,3,OB,B1,4,B2,5), and envelope (3E,4E,E3,E4) conformations into the yeast ERManI active site. Both docked energies and forces on docked ligand atoms were calculated to determine how the ligand distorts to the transition state. From these, we can conclude that (1) both 1C4 and OS2 can be the starting conformers; (2) the most likely binding pathway is 1C4-->3H2-->OS2-->3,OB-->3S1-->3E; (3) the transition state is likely to be close to a 3E conformation.